Triple
T5187940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German Cross in Silver |
E117077
|
entity |
| Predicate | combatOrNonCombat |
P61973
|
FINISHED |
| Object | non-combat |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: non-combat | Statement: [German Cross in Silver, combatOrNonCombat, non-combat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: combatOrNonCombat Context triple: [German Cross in Silver, combatOrNonCombat, non-combat]
-
A.
nonCombatHeroismScope
Indicates the extent or context in which acts of heroism occur outside of direct combat or fighting situations.
-
B.
introducedToCombat
Indicates that something was brought into use or implemented specifically for the purpose of addressing or mitigating a particular problem, threat, or undesirable condition.
-
C.
combatantsIncluded
Indicates that the specified entities are participants or parties involved in a particular combat or conflict.
-
D.
sawCombat
Indicates that an entity directly participated in active military or armed conflict.
-
E.
combatArm
Indicates that one entity serves as a primary fighting or operational warfare branch or component of another entity (such as an organization or military force).
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69bd44620ff48190bcac01782107a397 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd79c56280819085926316f7b520bc |
completed | March 20, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69bd77b7e8b4819092ec3965e11f2dea |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd78d6a1388190804dcf568ca92129 |
completed | March 20, 2026, 4:41 p.m. |
Created at: March 20, 2026, 1:46 p.m.